Integrated Communication & Remote Sensing Architecture

• Integrated communication and remote sensing architecture is a unified system that combines SAR imaging and broadband data transfer on a single transceiver platform.
• It leverages ODDM waveforms and synchronized TDD slots to jointly support high-resolution remote sensing and efficient communications, particularly in high-mobility LEO environments.
• The design simplifies hardware complexity, improves resource efficiency, and demonstrates enhanced performance through joint signal processing and optimized pilot structures.

Integrated communication and remote sensing architecture refers to a unified system design in which information transmission (communications) and environment probing (remote sensing, exemplified by radar and SAR) share hardware platforms, physical resources, and signal/processing chains. Such architectures are particularly vital in high-mobility and high-frequency environments—like LEO satellite networks—where resource efficiency, hardware simplicity, and operational flexibility are paramount. A prominent instantiation is detailed in (Xu et al., 14 Aug 2025), which integrates synthetic aperture radar (SAR)-based remote sensing and broadband user communication in LEO satellites via a unified waveform and transceiver stack.

1. Unified System Architecture

The architecture comprises a satellite payload embedding a single integrated transceiver (RF front-end and signal chain), supporting both SAR imaging and data communications within a common physical platform. This circuitry handles digitization (ADC/DAC), digital mapping, modulation/demodulation, cyclic prefix management, and I/Q up/downconversion for both uplink and downlink. The physical layer is based on Orthogonal Delay-Doppler Division Multiplexing (ODDM), which forms the basis for joint communications and radar operations. Both downlink (for SAR illumination/communication) and echo reception occur within precise TDD schedule slots, ensuring real-time SAR operation and broadband data transfer.

In detail, the transmitter uses digital mapping and ODDM modulation, passes through CP insertion and analog/RF upconversion, with the signal broadcast toward ground terminals and illuminated sensing regions. The receiver intakes RF signals, executes low-noise amplification and I/Q conversion, removes the CP, performs ODDM demodulation, and splits output into data and pilot streams for further distinct, but unified, processing.

This joint transceiver obviates SAR/comm waveform separation and enables a fully integrated hardware stack, minimizing volume, cost, and complexity onboard satellites with critical payload constraints ((Xu et al., 14 Aug 2025), Fig. 6).

2. ODDM Waveform Structure and Properties

Orthogonal delay-Doppler division multiplexing (ODDM) forms the physical-layer waveform foundation. The ODDM signal is synthesized over an $M \times N$ grid in the delay-Doppler (DD) domain, using modulated DD-domain orthogonal pulses (DDOPs) as the orthonormal basis:

$$s(t) = \sum_{m=0}^{M-1}\sum_{n=-(N/2)}^{N/2-1} X[m,n]\; g(t - m\mathcal{T}) \; e^{j2\pi n\mathcal{F}(t-m\mathcal{T})}$$

where $X[m,n]$ are DD-domain information or pilot symbols, $g(t)$ the DDOP achieving joint delay/Doppler orthogonality, $\mathcal{T}$ the delay spacing, and $\mathcal{F}$ the Doppler frequency spacing. For $M=1$ the design collapses to an OFDM waveform.

This structure allows both pilot (SAR probe) and data (comm) symbols to coexist on the same resource grid. The signal is inherently robust to both multipath delay spread and Doppler, which are prominent in LEO satellite channels. The underlying delay-Doppler grid directly maps to SAR image dimensions, ensuring the high-range and Doppler resolution required for remote sensing, while sustaining communications performance.

3. Protocol Design: Joint Communication and SAR

An ODDM-compatible frame and slot structure is designed with 5G NR compliance. Each frame, of duration $L_0$, is partitioned into $d$ slots (with $d=10 \times 2^{\mu}$, $\mu$ the numerology index). In downlink slots, pilots are periodically inserted (e.g., every $n_0$ slots), serving as both channel estimation reference for communication and as SAR illumination pulses. Data symbols are mapped into the remaining grid points.

The pilot pattern in the DD-domain is engineered for IRCI-free (inter-range-cell interference–free) SAR imaging. The pilot vector $u_m$ (Zadoff-Chu-type) occupies the first delay bin per slot; guard regions protect against inter-slot leakage. The same pilots are utilized at the receiver for both channel estimation and radar return analysis.

Uplink slots are also supported but primarily for user terminal data; SAR operates primarily in downlink-echo mode.

4. Unified Signal Processing at the Receiver

The satellite receiver implements a joint processing framework that addresses channel estimation, equalization, and range reconstruction as follows:

• Channel Sensing (DD-domain): From received pilot columns, a delay-Doppler channel matrix $H^{\star}$ is estimated. The estimation procedure leverages the periodic pilot structure and uses FFT/inverse FFT for efficient computation. The estimator is designed to minimize noise amplification, with optimal performance given by an MSE of $\sigma^2/E_0$ (input noise over pilot energy), achieved uniquely by constant-modulus (e.g., ZC) sequences.
• MMSE Equalization (Communications): Data symbols on DD grid points are equalized using a low-complexity MMSE filter

$$\mathbf{W} = \tilde{H}_n^H (\tilde{H}_n \tilde{H}_n^H + \sigma^2 I_M)^{-1}$$

where $\tilde{H}_n$ is derived from the DD-domain channel estimate, and the equalized symbols are demapped and decoded for user communications.

• SAR Range Profile and Imaging: The same $H^{\star}$ is matched filtered to extract range cell echo coefficients $\hat\beta_q$ via

$$r_{rc}(t, \eta) = \sum_q \hat{\beta}_q(\eta) \; \delta(t - 2R_q/c)$$

enabling range-Doppler imaging. The pipeline supports migration correction, azimuth compression, and autofocus to achieve high-resolution SAR images, with theoretical and empirical evidence of no IRCI due to the pilot/pulse design.

The architecture thus allows concurrent, low-latency SAR image formation and continuous or bursty broadband user data reception.

5. Performance Evaluation and Hardware Prototyping

Simulation and analysis in the sub-6 GHz band demonstrate that:

• Channel estimation MSE is minimized with ZC pilot sequences, outperforming single-pilot or PN-based designs.
• BER performance: Uncoded ODDM achieves a 2.1 dB performance gain over OFDM at $10^{-5}$ BER (with similar advantage in coded settings), under the same spectral efficiency.
• SAR imaging: The proposed technique yields IRCI-free range reconstruction, with PSF plots confirming orders of magnitude suppression of sidelobes compared to conventional LFM/matched filtering. The processed echo SINR is improved by a factor $MN$ when using constant-modulus pilots.
• Hardware validation: An SDR prototype utilizing USRP-X410, 28 GHz mmWave phased arrays, and 5G mmWave converter demonstrates, in direct transmission from a LEO emulation node, real-time joint SAR imaging and user data reception, achieving 0.61 m range and 0.77 m azimuth resolution.

6. Architectural Impact and Design Trade-offs

The integrated architecture achieves:

• Unified hardware utilization: Common RF, ADC/DAC, and baseband for comms and sensing, simplifying the payload.
• Resource efficiency: Shared spectrum and temporal resources maximize throughput and sensing coverage without additional hardware or bandwidth.
• Protocol compatibility: The adopted signaling and pilot structure remain compatible with 5G NR, facilitating cross-standard deployments.

Trade-offs are managed through:

• Pilot frequency: Sufficient pilot periodicity supports SAR PRF requirements; excessive pilot insertion reduces communications payload.
• Joint waveform optimization: Selection of ODDM parameters enables balancing resolution (for SAR) with robust communications in doubly dispersive channels.
• Processing complexity: Unified pipeline reduces overall computational burden through FFT-based operations and matrix-based equalization/sensing.

7. Prospective Extensions and Context

The demonstrated architecture (Xu et al., 14 Aug 2025) substantiates the feasibility and value of joint communication and remote sensing in satellite networks:

• Extensible to other physical-layer multiplexing schemes with compatible time-frequency structure.
• Adaptable for real-time disaster monitoring, direct-to-device broadband, as well as coordinated vehicular observation (in conjunction with ICNR frameworks (Sheng et al., 17 Apr 2024)).
• The architecture points to further research in optimizing ODDM grid parameters, multi-user and multi-target scaling, and robust synchronization in realistic LEO environments.

The combination of protocol design, architecture, unified receiver processing, and hardware validation advances the integrated communication and remote sensing paradigm from theoretical feasibility to operational demonstration in realistic LEO satellite scenarios.